Interference cancellation is crucial to the performance of User Equipment (UE) in wireless access network. In 3rd Generation Partnership Project (3GPP) Rel-12, Physical downlink shared channel (PDSCH) and (enhanced) Physical Downlink Control Channel ((e)PDCCH) cancellation is under development. How to cancel interference on PDSCH and (e)PDCCH is quite open.
In 3GPP, interference cancellation has been widely discussed. In Rel-11, Cell specific Reference Signal Interference Cancellation (CRS-IC), Primary Synchronization Signal (PSS)/Secondary Synchronization Signal (SSS), IC and Physical Broadcast CHannel (PBCH) IC has been standardized for heterogeneous networks. To enhance User Equipment (UE) performance, PDSCH and PDCCH/ePDCCH IC are under discussion in Rel-12. In Rel-11, in order to enable CRS-IC, PSS/SSS, and PBCH IC, an evolved Node B (eNB) needs to provide certain assistance information, including CRS ports, cell ID, and Multimedia Broadcast multicast service Single Frequency Network (MBSFN) configuration. A UE utilizes this information to cancel interference from CRS, PSS/SSS and PBCH. In Rel-12, how to enhance UE performance by interference cancellation from data channels has not been determined.
A brief introduction of terminology used throughout the specifications is presented here. The term Serving Cell (SC) is understood to encompass the cell to which the UE is currently attached, and Neighbouring Cell (NC) is understood to encompass a cell or transmission points where the transmission of data is typically interfering with the reception of data from the SC. Interference Cancellation (IC) is understood to encompass regeneration and subtraction of interfering data or control signalling from the desired received signal. Typical types of IC are soft IC and hard IC, which are discussed below, but IC receivers also include maximum likelihood (ML) type receivers. Unless otherwise noted, any reference to an “IC receiver” or “IC processing” herein shall be understood as referring to some type of assisted-mode processing. A baseline receiver is here understood to refer to a receiver that does not use assisted-mode interference cancellation and may be, for example, a “legacy” Rel-11 receiver using e.g. Linear Minimum Mean Square Error (LMMSE)-IRC processing.
A Network-Assisted Interference Cancelation and Suppression (NAICS) receiver is understood to encompass an interference cancellation or suppression capable receiver that can be one of several types discussed below, and which operates in assisted mode and thus uses assistance information for interference cancellation. An assisted-mode receiver is here understood to represent a NAICS receiver, or other such receiver, that uses assistance information to cancel or suppress interference for one or more interfering signals in a received signal. A non-assisted mode receiver is here understood to represent a receiver that may (but not necessarily does) perform interference cancellation, but does so without using assistance information.
For network-assisted interference cancellation and suppression, different interference mitigation methods can be used. Two kinds of IC methods are extensively discussed. One is Symbol Level Interference Cancelation (SLIC), and the other is CodeWord level Interference Cancelation (CWIC). For symbol level interference cancellation, the interference signal is regenerated after demodulation and further subtracted from the receiving signal. For code word level interference cancellation, the interference signal is synthesized after channel decoding, and further subtracted from the receiving signal. The main interference suppression method that has been discussed is Enhanced-IRC, which is an IRC receiver where the interference covariance matrix is parametrically built. There is also a fourth interference mitigation algorithm that has been studied, which is the Maximum Likelihood (ML) receiver, where the best modulation symbol is found according to a given interference distribution.
Quite common for any kind of effective interference cancellation algorithm is that it is a soft IC. This means that it will take the certainty of a certain symbol value, or parameter value into account when determining how to regenerate and cancel the transmitted information. For example, when there is a lot of interference or noise on the data stream to be cancelled, the quality of demodulation and/or decoding can be expected to be low, and then typically the regenerated data symbols are created with lower energy to only cancel the certain part of the symbol and not introduce a lot of additional errors. If this is done correctly, then soft IC should never introduce additional errors or interference in the cancellation step.
Unfortunately, as discussed below, there are always cases where the soft IC algorithm is unaware of uncertainty or parameter errors and therefore cannot avoid errors. The soft IC is a generalization of the hard IC, where in the latter symbol regeneration is limited to the set of transmitted modulation symbols. In the following discussion we will only use the more general soft IC, but it can easily be translated also to the hard IC case.
The ML receiver is another kind of hard decision interference mitigation algorithm which also has a soft counterpart. For ML, the hard decision is made over several layers at once. Similar arguments discussed for soft IC also hold for ML receiver, hence in the following discussion about drawbacks for soft IC will also hold for ML receiver. CRS IC is a specific version of hard IC, where the regenerated symbol is only regenerated to already the known symbol value of the pilot.
To facilitate the interference estimation and regeneration at the UE side, firstly, a network provides to the UEs information about transmission properties of interfering signals so that the UEs can estimate channel status of the interferers that are intended to be cancelled. Secondly, depending on the UE's capability, the structure of interfering signals, such as modulation style/feature (for instance modulation order), may be needed to be known to the UE. Additional information on this interference signal structure, including the consistency of the structure during a size of scheduling resource granularity, can aid the UE to efficiently estimate and synthesize the interfering signal with a low complexity, which is a critical factor for standardization and product's business value.
In short, network assistance is preferably to provide information about the interferers, including any information aiding the UEs to infer interfering channel status and information on the structure or features of the interfering signal.
Network assistance always comes with a cost to the system, since it consumes valuable system resource when being transmitted to the receiver. Therefore, it is expected that a NAICS receiver will have to blindly detect, i.e. estimate one or more transmission parameters based on received signal properties, quite a few of the NC parameters, often based on statistics on the received data signal.
The typical processing steps of a NAICS receiver using blind detection and IC is shown in FIG. 1, which shows the typical processing steps of a NAICS receiver using IC and blind detection. Here, to select the best decoding result encompasses picking a decoding result with a Cyclic Redundancy Check (CRC) that indicates no data corruption.
A typical IC receiver takes information on Signal-to-Interference-plus-Noise Ratio (SINR) levels into account when cancelling data in order to avoid hard decisions that add interference rather than reducing it. As long as the receiver has correct information about the current noise level and NC parameters, this IC can be done essentially without loss in any case. This is shown in FIG. 2, showing the cancellation efficiency (fraction of cancelled interfering energy) versus the Signal-to-Noise-Ratio (SNR) when the receiver has perfect knowledge about the NC channel, noise level, modulation and other parameters. As can be noted, there is almost no instances of negative CE, i.e. increased interference rather than reduced.
In practice, though, the receiver will have to rely in estimated data both for channel and noise level as well as for other NC parameters such as modulation. In FIG. 3 and FIG. 4, two examples of the impact of errors in this estimation are shown. This can lead to worse performance in the receiver with a NAICS receiver than in the baseline receiver at certain operating points. This can also easily be verified in simulations. For example, when the quality of channel estimates is too low or when blind detection of NC parameters fail, the IC performance is quite often worse than for the baseline receiver.
FIG. 3 shows the cancellation efficiency when 16QAM is assumed on the NC in all cases, but the real NC modulation is as defined in the legend. For 16QAM and 64QAM, this works fine, but for QPSK it actually adds significant interference (negative CE) around SNR 10 dB. FIG. 4 shows the CE when the SNR estimate in the receiver is optimistic and has a scaling error of 0.5 (−3 dB). It should be noted that interference created by the IC is added around the 0 dB region.